Geek Think: How Scientists Approach the World

Almost there, aren’t we? Congratulations. Now, at last, it is time to consider why you have been taking this class.

A few facts about chemistry is one good reason. Learning how to think like a scientist is the other.

Today we will be addressing the second point, the fine art of honing the geek mind. We will approach this subject by example, by going through the experiment that was assigned a couple of sessions ago. The following little piece constitutes my own effort at completing the task, with a few editorial comments thrown into spice the stew. Naturally in the normal order of things all of this would be recorded in a laboratory notebook so that you could sign and date the entries, to protect your important insights from competitors in the Alka-Seltzer analysis field. You will just have to settle for reading about it on line.

Let’s start with HYPOTHESES. I came up with two:

Two-tailed: Altering the reaction temperature will alter the reaction rate.

One-Tailed: The reaction will increase as the reaction temperature rises.

A two-tailed hypothesis is one that makes no assumption about what outcome will occur (i.e., a rising reaction temperature will alter the rate either up or down), while a one-tailed hypothesis picks a specific way in which you think the outcome may trend.

The next thing a good experiment needs is a list of MATERIALS. I include separate headings for reagents (the stuff that participates in and/or is consumed during the chemical reaction – in this case Alka-Seltzer and water) and equipment to perform the experiment (clear glass, 1-cup measuring cup, watch with second hand, thermometer). The materials list is followed by a really detailed, step-by-step set of METHODS. One must pay great attention to detail in this section so that (1) you can catch any mistakes you have made in running the experiment and (2) so that other people can replicate your work. In science, if it can’t be repeated is not considered reputable. The methods I used for this experiment were, in order, the following:

1. Alka-Seltzer tablets were unwrapped two at a time.

2. Water was prepared as follows:

a. Cold (~0°C): Four 1-in³ ice cubes were added to four cups of water and left for 15 minutes

b. Normal (~20°C) Four cups of water were decanted from a receptacle after sitting for 24 hours at room temperature

c. Hot (~100°C) Four cups of tap water were heated to boiling in a teapot

3. The glass was equilibrated to the desired water temperature by pre-filling with either ice water or hot water.

4. One cup of water at the appropriate temperature was placed in the glass. A 1-in³ ice cube was added to the “cold trials” to keep the water cold.

5. A single tablet was dropped from a 2-inch height into the vessel.

6. Time (in seconds) to complete dissolution of the primary tablet (i.e., the end of violent fizzing) was recorded.

7. Ancillary (“other”) measurements included observations on tablet motility and gas evolution.

Of course, the point of an experiment is to get some RESULTS. These are the ones I got. I put them into a table so that the raw data (the values measured during all the trials) would be available for inspection. Then I calculated the mean (the average) of the results for each temperature so that someone wanting to quickly see the outcome would be able to do so at a glance.

	Temperature
Trial	0°C	20°C	100°C
1	87 s	47 s	34 s
2	100 s	45 s	33 s
3	80 s	49 s	32 s
4	66 s	49 s	32 s
Mean	**83	48	**33
SD	14	2	1

The double asterisks (**) denote that the mean values for these two groups are significantly different from the mean value for the 20°C group, p < style=""> (Normally, statistical significance is assigned to an outcome if p <>

I made a few additional observations on characteristics of Alka-Seltzer. These traits were not the focus of my hypotheses, so I did not measure them exactly. However, I made some reasonable “guesstimates” regarding their repeatability so that I could investigate them in more detail.

1. Tablet motility varied by temperature. Tablet orientation became:

a. Cold (~0°C): Vertical at 45 to 50 s

Floated at 55 to 60 s

b. Normal (~20°C) Vertical at 15 to 20 s

Floated at 20 to 25 s

c. Hot (~100°C) Vertical orientation not seen

Floated immediately

2. Tablet character upon cessation of fizzing.

a. Cold (~0°C): Many small particles and much foam cover most of the surface

b. Normal (~20°C) A few fine particles and some foam line the rim of the glass

c. Hot (~100°C) No particles or foam remain

3. Gas evolution varied by temperature.

a. Cold (~0°C): Fine bubbles made from top of tablet, large ones from beneath

b. Normal (~20°C) Fine bubbles made from top and bottom of tablet

c. Hot (~100°C) Myriad fine bubbles from entire surface of tablet, as well as elaboration of steam from upper surface

Finally, you use the results to make an INTERPRETATION. This step is also called drawing conclusions or making inferences. In this case, my results confirmed the hypotheses I made: the rate of a chemical reaction is significantly increased as the reaction temperature is raised.

A word on STATISTICS. Mark Twain popularized the Benjamin Disraeli proverb, “There are three kinds of lies: lies, damned lies, and statistics.” This statement is knocking statistics, but those who would use a mass of poorly understand numbers – even if correctly calculated – to support an inaccurate conclusion. Scientists rely on statistics to avoid false positive and false negative conclusions. A false positive or Type I error occurs when the statistical calculation suggests that something is of significance but in reality it is not, while a false negative or Type II error occurs when something significant in the real world is not identified as such using the statistical analysis. In general, scientists tend to try to avoid the Type I error more vigorously. A detailed consideration of statistics s way, way, way beyond the scope of this blog. Just keep in mind that statistical calculations can be used by different scientists working on the same problem to bolster totally opposite points of view. Just because a number is thrown at you, don’t believe that the “answer” it is trying to reinforce is true. The concept caveat emptor – “Let the buyer beware” – is particularly true in science. Be open to new ideas, but be skeptical about adopting them without a thorough review of the data for yourself.

Sleep tight. It all ends tomorrow. The class, I mean….